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http://dx.doi.org/10.7465/jkdi.2013.24.6.1263

Validity assessment of VaR with Laplacian distribution  

Byun, Bu-Guen (Department of Electronic, Information, and Communication Engineering, Hongik University)
Yoo, Do-Sik (Department of Electronic, Information, and Communication Engineering, Hongik University)
Lim, Jongtae (Department of Electrical, Information, and Control Engineering, Hongik University)
Publication Information
Journal of the Korean Data and Information Science Society / v.24, no.6, 2013 , pp. 1263-1274 More about this Journal
Abstract
VaR (value at risk), which represents the expectation of the worst loss that may occur over a period of time within a given level of confidence, is currently used by various financial institutions for the purpose of risk management. In the majority of previous studies, the probability of return has been modeled with normal distribution. Recently Chen et al. (2010) measured VaR with asymmetric Laplacian distribution. However, it is difficult to estimate the mode, the skewness, and the degree of variance that determine the shape of an asymmetric Laplacian distribution with limited data in the real-world market. In this paper, we show that the VaR estimated with (symmetric) Laplacian distribution model provides more accuracy than those with normal distribution model or asymmetric Laplacian distribution model with real world stock market data and with various statistical measures.
Keywords
Asymmetric Laplacian distribution; KOSPI; Laplacian distribution; parametric estimation; value at risk;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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